corresponding to a situation where the features are independent and that their distribution under their null is continuous [1]}. Under \(H_0\) , \(-2\log (p_i)\)  has a chisquared distribution with two degrees of freedom \(\chi _2^2\) , aka the exponential distribution with mean 2. Our model proposes the following alternative: Roughly \(n\epsilon \)  of the P-values depart from their uniform distribution and instead obey
\(-2\log (p_i) \overset{D}{\approx } \left( \mu + \sigma Z\right)^2,\qquad Z\sim \mathcal {N}(0,1).\) 
